Pandas Profiling Report

Dataset statistics

Number of variables	22
Number of observations	95
Missing cells	0
Missing cells (%)	0.0%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	16.5 KiB
Average record size in memory	177.3 B

Variable types

Numeric	12
Categorical	10

Alerts

`city` has constant value "Lahore"	Constant
`province_name` has constant value "Punjab"	Constant
`purpose` has constant value "For Sale"	Constant
`page_url` has a high cardinality: 95 distinct values	High cardinality
`property_id` is highly overall correlated with `location_id` and 7 other fields	High correlation
`location_id` is highly overall correlated with `property_id` and 11 other fields	High correlation
`price` is highly overall correlated with `page_url` and 8 other fields	High correlation
`latitude` is highly overall correlated with `location_id` and 8 other fields	High correlation
`longitude` is highly overall correlated with `property_id` and 13 other fields	High correlation
`baths` is highly overall correlated with `location_id` and 12 other fields	High correlation
`area_marla` is highly overall correlated with `page_url` and 8 other fields	High correlation
`area_sqft` is highly overall correlated with `page_url` and 8 other fields	High correlation
`bedrooms` is highly overall correlated with `page_url` and 10 other fields	High correlation
`year` is highly overall correlated with `month`	High correlation
`month` is highly overall correlated with `location_id` and 8 other fields	High correlation
`day` is highly overall correlated with `property_id` and 10 other fields	High correlation
`page_url` is highly overall correlated with `property_id` and 16 other fields	High correlation
`property_type` is highly overall correlated with `page_url` and 4 other fields	High correlation
`price_bin` is highly overall correlated with `location_id` and 8 other fields	High correlation
`location` is highly overall correlated with `property_id` and 16 other fields	High correlation
`locality` is highly overall correlated with `property_id` and 16 other fields	High correlation
`area` is highly overall correlated with `property_id` and 16 other fields	High correlation
`date_added` is highly overall correlated with `property_id` and 15 other fields	High correlation
`page_url` is uniformly distributed	Uniform
`property_id` has unique values	Unique
`page_url` has unique values	Unique
`baths` has 16 (16.8%) zeros	Zeros
`bedrooms` has 12 (12.6%) zeros	Zeros

Reproduction

Analysis started	2022-12-04 22:47:28.770237
Analysis finished	2022-12-04 22:47:47.852909
Duration	19.08 seconds
Software version	pandas-profiling vv3.5.0
Download configuration	config.json

property_id
Real number (ℝ)

HIGH CORRELATION
UNIQUE

Distinct	95
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	3371864.1

Minimum	347795
Maximum	5019310
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	888.0 B

Quantile statistics

Minimum	347795
5-th percentile	983065.7
Q1	2471475
median	3931998
Q3	4323660
95-th percentile	4698194.6
Maximum	5019310
Range	4671515
Interquartile range (IQR)	1852185

Descriptive statistics

Standard deviation	1176444.8
Coefficient of variation (CV)	0.34890042
Kurtosis	-0.26253121
Mean	3371864.1
Median Absolute Deviation (MAD)	625801
Skewness	-0.8067837
Sum	3.2032709 × 10⁸
Variance	1.3840224 × 10¹²
Monotonicity	Strictly increasing

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
347795	1	1.1%
4017113	1	1.1%
4304977	1	1.1%
4249571	1	1.1%
4170552	1	1.1%
4159826	1	1.1%
4153988	1	1.1%
4111694	1	1.1%
4107715	1	1.1%
4100382	1	1.1%
Other values (85)	85	89.5%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
347795	1	1.1%
482892	1	1.1%
555962	1	1.1%
785289	1	1.1%
983065	1	1.1%
983066	1	1.1%
1286643	1	1.1%
1402784	1	1.1%
1606710	1	1.1%
1646880	1	1.1%

Value	Count	Frequency (%)
5019310	1	1.1%
4951451	1	1.1%
4940629	1	1.1%
4907568	1	1.1%
4747413	1	1.1%
4677101	1	1.1%
4570988	1	1.1%
4560911	1	1.1%
4557799	1	1.1%
4536854	1	1.1%

location_id
Real number (ℝ)

Distinct	55
Distinct (%)	57.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	5125.2947

Minimum	7
Maximum	10542
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	888.0 B

Quantile statistics

Minimum	7
5-th percentile	73.2
Q1	1604
median	3847
Q3	9433
95-th percentile	9436
Maximum	10542
Range	10535
Interquartile range (IQR)	7829

Descriptive statistics

Standard deviation	3727.3855
Coefficient of variation (CV)	0.72725291
Kurtosis	-1.6461484
Mean	5125.2947
Median Absolute Deviation (MAD)	3474
Skewness	0.099539953
Sum	486903
Variance	13893403
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
9435	9	9.5%
9434	6	6.3%
9433	6	6.3%
8172	5	5.3%
9436	4	4.2%
1784	3	3.2%
10542	3	3.2%
514	3	3.2%
9432	3	3.2%
3824	2	2.1%
Other values (45)	51	53.7%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
7	1	1.1%
8	2	2.1%
48	1	1.1%
69	1	1.1%
75	1	1.1%
154	2	2.1%
373	1	1.1%
377	1	1.1%
378	1	1.1%
496	1	1.1%

Value	Count	Frequency (%)
10542	3	3.2%
9747	1	1.1%
9436	4	4.2%
9435	9	9.5%
9434	6	6.3%
9433	6	6.3%
9432	3	3.2%
8444	1	1.1%
8425	1	1.1%
8172	5	5.3%

page_url
Categorical

HIGH CARDINALITY
HIGH CORRELATION
UNIFORM
UNIQUE

Distinct	95
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Memory size	888.0 B

https://www.zameen.com/Property/lahore_model_town_6_kanal_excellent_house_for_sale_in_model_town-347795-8-1.html	1
https://www.zameen.com/Property/dha_defence_defence_raya_1_kanal_house_for_sale_at_facing_golf_park_dha_raya-4017113-8172-1.html	1
https://www.zameen.com/Property/dha_defence_dha_phase_4_house_for_sale_in_dha_phase_4-4304977-1446-1.html	1
https://www.zameen.com/Property/gulberg_gulberg_4_exclusive_location_house_for_sale-4249571-3847-1.html	1
https://www.zameen.com/Property/allama_iqbal_town_allama_iqbal_town_pak_block_2_marla_double_storey_house_for_sale-4170552-3527-1.html	1
Other values (90)	90

Length

Max length	165
Median length	135
Mean length	124.85263
Min length	88

Characters and Unicode

Total characters	11861
Distinct characters	42
Distinct categories	6 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	95 ?
Unique (%)	100.0%

Sample

1st row	https://www.zameen.com/Property/lahore_model_town_6_kanal_excellent_house_for_sale_in_model_town-347795-8-1.html
2nd row	https://www.zameen.com/Property/lahore_multan_road_1_kanal_house_for_sale-482892-48-1.html
3rd row	https://www.zameen.com/Property/eden_eden_avenue_9_marla_house_for_sale-555962-75-1.html
4th row	https://www.zameen.com/Property/gulberg_paf_falcon_complex_matz_service_offer_1_kanal_house_for_sale-785289-3102-1.html
5th row	https://www.zameen.com/Property/eme_society_eme_society_block_e_house_for_sale-983065-3749-1.html

Common Values

Value	Count	Frequency (%)
https://www.zameen.com/Property/lahore_model_town_6_kanal_excellent_house_for_sale_in_model_town-347795-8-1.html	1	1.1%
https://www.zameen.com/Property/dha_defence_defence_raya_1_kanal_house_for_sale_at_facing_golf_park_dha_raya-4017113-8172-1.html	1	1.1%
https://www.zameen.com/Property/dha_defence_dha_phase_4_house_for_sale_in_dha_phase_4-4304977-1446-1.html	1	1.1%
https://www.zameen.com/Property/gulberg_gulberg_4_exclusive_location_house_for_sale-4249571-3847-1.html	1	1.1%
https://www.zameen.com/Property/allama_iqbal_town_allama_iqbal_town_pak_block_2_marla_double_storey_house_for_sale-4170552-3527-1.html	1	1.1%
https://www.zameen.com/Property/allama_iqbal_town_allama_iqbal_town_pak_block_2_marla_house_is_available_for_sale-4159826-3527-1.html	1	1.1%
https://www.zameen.com/Property/bahria_town_sector_c_bahria_town_tulip_block_10_marla_brand_new_house_in_sector_c_bahria_town_lahore-4153988-1789-1.html	1	1.1%
https://www.zameen.com/Property/dha_phase_5_dha_phase_5_block_a_1_kanal_beautiful_bungalow_house_for_sale-4111694-1598-1.html	1	1.1%
https://www.zameen.com/Property/dha_defence_dha_phase_6_1_kanal_brand_new_beautiful_bungalow_for_sale-4107715-1448-1.html	1	1.1%
https://www.zameen.com/Property/askari_10_askari_10_sector_f_17_marla_corner_brand_new_brig_house_available_for_sale-4100382-10542-1.html	1	1.1%
Other values (85)	85	89.5%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
https://www.zameen.com/property/lahore_model_town_6_kanal_excellent_house_for_sale_in_model_town-347795-8-1.html	1	1.1%
https://www.zameen.com/property/askari_10_askari_10_sector_b_one_kanal_house_khalid_designed_main_boulevard_fully_renovated_available_for_sale-2471472-9433-1.html	1	1.1%
https://www.zameen.com/property/eden_eden_avenue_9_marla_house_for_sale-555962-75-1.html	1	1.1%
https://www.zameen.com/property/gulberg_paf_falcon_complex_matz_service_offer_1_kanal_house_for_sale-785289-3102-1.html	1	1.1%
https://www.zameen.com/property/eme_society_eme_society_block_e_house_for_sale-983065-3749-1.html	1	1.1%
https://www.zameen.com/property/eme_society_eme_society_block_a_house_for_sale-983066-3745-1.html	1	1.1%
https://www.zameen.com/property/eden_eden_palace_villas_7_5_marla_luxury_house_is_available_for_sale-1286643-3733-1.html	1	1.1%
https://www.zameen.com/property/lahore_upper_mall_commercial_old_house_for_sale_upper_mall_lahore_excellent_location-1402784-514-1.html	1	1.1%
https://www.zameen.com/property/lahore_cavalry_ground_10_marla_house_is_available_for_sale-1606710-69-1.html	1	1.1%
https://www.zameen.com/property/bahria_town_sector_b_bahria_town_umar_block_double_storey_house_for_sale-1646880-1781-1.html	1	1.1%
Other values (85)	85	89.5%

Most occurring characters

Value	Count	Frequency (%)
_	1181	10.0%
a	917	7.7%
e	904	7.6%
r	671	5.7%
o	605	5.1%
t	557	4.7%
l	531	4.5%
s	475	4.0%
m	419	3.5%
/	380	3.2%
Other values (32)	5221	44.0%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	8173	68.9%
Decimal Number	1367	11.5%
Connector Punctuation	1181	10.0%
Other Punctuation	760	6.4%
Dash Punctuation	285	2.4%
Uppercase Letter	95	0.8%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
a	917	11.2%
e	904	11.1%
r	671	8.2%
o	605	7.4%
t	557	6.8%
l	531	6.5%
s	475	5.8%
m	419	5.1%
h	376	4.6%
n	349	4.3%
Other values (16)	2369	29.0%

Decimal Number

Value	Count	Frequency (%)
1	320	23.4%
4	178	13.0%
3	150	11.0%
0	145	10.6%
9	118	8.6%
5	105	7.7%
2	104	7.6%
7	101	7.4%
8	86	6.3%
6	60	4.4%

Other Punctuation

Value	Count	Frequency (%)
/	380	50.0%
.	285	37.5%
:	95	12.5%

Connector Punctuation

Value	Count	Frequency (%)
_	1181	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	285	100.0%

Uppercase Letter

Value	Count	Frequency (%)
P	95	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	8268	69.7%
Common	3593	30.3%

Most frequent character per script

Latin

Value	Count	Frequency (%)
a	917	11.1%
e	904	10.9%
r	671	8.1%
o	605	7.3%
t	557	6.7%
l	531	6.4%
s	475	5.7%
m	419	5.1%
h	376	4.5%
n	349	4.2%
Other values (17)	2464	29.8%

Common

Value	Count	Frequency (%)
_	1181	32.9%
/	380	10.6%
1	320	8.9%
.	285	7.9%
-	285	7.9%
4	178	5.0%
3	150	4.2%
0	145	4.0%
9	118	3.3%
5	105	2.9%
Other values (5)	446	12.4%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	11861	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
_	1181	10.0%
a	917	7.7%
e	904	7.6%
r	671	5.7%
o	605	5.1%
t	557	4.7%
l	531	4.5%
s	475	4.0%
m	419	3.5%
/	380	3.2%
Other values (32)	5221	44.0%

property_type
Categorical

Distinct	2
Distinct (%)	2.1%
Missing	0
Missing (%)	0.0%
Memory size	888.0 B

House	93
Flat	2

Length

Max length	5
Median length	5
Mean length	4.9789474
Min length	4

Characters and Unicode

Total characters	473
Distinct characters	9
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	House
2nd row	House
3rd row	House
4th row	House
5th row	House

Common Values

Value	Count	Frequency (%)
House	93	97.9%
Flat	2	2.1%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
house	93	97.9%
flat	2	2.1%

Most occurring characters

Value	Count	Frequency (%)
H	93	19.7%
o	93	19.7%
u	93	19.7%
s	93	19.7%
e	93	19.7%
F	2	0.4%
l	2	0.4%
a	2	0.4%
t	2	0.4%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	378	79.9%
Uppercase Letter	95	20.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
o	93	24.6%
u	93	24.6%
s	93	24.6%
e	93	24.6%
l	2	0.5%
a	2	0.5%
t	2	0.5%

Uppercase Letter

Value	Count	Frequency (%)
H	93	97.9%
F	2	2.1%

Most occurring scripts

Value	Count	Frequency (%)
Latin	473	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
H	93	19.7%
o	93	19.7%
u	93	19.7%
s	93	19.7%
e	93	19.7%
F	2	0.4%
l	2	0.4%
a	2	0.4%
t	2	0.4%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	473	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
H	93	19.7%
o	93	19.7%
u	93	19.7%
s	93	19.7%
e	93	19.7%
F	2	0.4%
l	2	0.4%
a	2	0.4%
t	2	0.4%

price
Real number (ℝ)

Distinct	64
Distinct (%)	67.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	78244211

Minimum	3200000
Maximum	1.25 × 10⁹
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	888.0 B

Quantile statistics

Minimum	3200000
5-th percentile	7190000
Q1	20750000
median	23500000
Q3	49750000
95-th percentile	3.66 × 10⁸
Maximum	1.25 × 10⁹
Range	1.2468 × 10⁹
Interquartile range (IQR)	29000000

Descriptive statistics

Standard deviation	1.9351258 × 10⁸
Coefficient of variation (CV)	2.4731872
Kurtosis	25.986397
Mean	78244211
Median Absolute Deviation (MAD)	11500000
Skewness	4.9270411
Sum	7.4332 × 10⁹
Variance	3.744712 × 10¹⁶
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
22500000	5	5.3%
23000000	5	5.3%
40000000	4	4.2%
23500000	4	4.2%
21500000	4	4.2%
35000000	3	3.2%
50000000	3	3.2%
22000000	3	3.2%
21000000	2	2.1%
3200000	2	2.1%
Other values (54)	60	63.2%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
3200000	2	2.1%
5500000	2	2.1%
6000000	1	1.1%
7700000	1	1.1%
8000000	1	1.1%
9500000	1	1.1%
11800000	1	1.1%
12000000	2	2.1%
12500000	1	1.1%
13500000	1	1.1%

Value	Count	Frequency (%)
1250000000	1	1.1%
1200000000	1	1.1%
620000000	1	1.1%
480000000	1	1.1%
380000000	1	1.1%
360000000	1	1.1%
220000000	1	1.1%
180000000	1	1.1%
160000000	1	1.1%
87500000	1	1.1%

price_bin
Categorical

Distinct	4
Distinct (%)	4.2%
Missing	0
Missing (%)	0.0%
Memory size	888.0 B

Very High	41
High	40
Low	8
Medium	6

Length

Max length	9
Median length	6
Mean length	6.2
Min length	3

Characters and Unicode

Total characters	589
Distinct characters	16
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Very High
2nd row	Very High
3rd row	Low
4th row	Very High
5th row	High

Common Values

Value	Count	Frequency (%)
Very High	41	43.2%
High	40	42.1%
Low	8	8.4%
Medium	6	6.3%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
high	81	59.6%
very	41	30.1%
low	8	5.9%
medium	6	4.4%

Most occurring characters

Value	Count	Frequency (%)
i	87	14.8%
H	81	13.8%
g	81	13.8%
h	81	13.8%
e	47	8.0%
V	41	7.0%
r	41	7.0%
y	41	7.0%
	41	7.0%
L	8	1.4%
Other values (6)	40	6.8%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	412	69.9%
Uppercase Letter	136	23.1%
Space Separator	41	7.0%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
i	87	21.1%
g	81	19.7%
h	81	19.7%
e	47	11.4%
r	41	10.0%
y	41	10.0%
o	8	1.9%
w	8	1.9%
d	6	1.5%
u	6	1.5%

Uppercase Letter

Value	Count	Frequency (%)
H	81	59.6%
V	41	30.1%
L	8	5.9%
M	6	4.4%

Space Separator

Value	Count	Frequency (%)
	41	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	548	93.0%
Common	41	7.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
i	87	15.9%
H	81	14.8%
g	81	14.8%
h	81	14.8%
e	47	8.6%
V	41	7.5%
r	41	7.5%
y	41	7.5%
L	8	1.5%
o	8	1.5%
Other values (5)	32	5.8%

Common

Value	Count	Frequency (%)
	41	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	589	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
i	87	14.8%
H	81	13.8%
g	81	13.8%
h	81	13.8%
e	47	8.0%
V	41	7.0%
r	41	7.0%
y	41	7.0%
	41	7.0%
L	8	1.4%
Other values (6)	40	6.8%

location
Categorical

Distinct	28
Distinct (%)	29.5%
Missing	0
Missing (%)	0.0%
Memory size	888.0 B

Askari	31
Gulberg	12
DHA Defence	10
Bahria Town	6
EME Society	5
Other values (23)	31

Length

Max length	36
Median length	24
Mean length	9.4526316
Min length	3

Characters and Unicode

Total characters	898
Distinct characters	43
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	17 ?
Unique (%)	17.9%

Sample

1st row	Model Town
2nd row	Multan Road
3rd row	Eden
4th row	Gulberg
5th row	EME Society

Common Values

Value	Count	Frequency (%)
Askari	31	32.6%
Gulberg	12	12.6%
DHA Defence	10	10.5%
Bahria Town	6	6.3%
EME Society	5	5.3%
Allama Iqbal Town	3	3.2%
Upper Mall	3	3.2%
Paragon City	2	2.1%
Model Town	2	2.1%
Eden	2	2.1%
Other values (18)	19	20.0%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
askari	31	20.8%
town	14	9.4%
gulberg	12	8.1%
dha	10	6.7%
defence	10	6.7%
society	8	5.4%
bahria	6	4.0%
eme	5	3.4%
housing	3	2.0%
allama	3	2.0%
Other values (32)	47	31.5%

Most occurring characters

Value	Count	Frequency (%)
a	88	9.8%
e	74	8.2%
r	66	7.3%
i	60	6.7%
	54	6.0%
n	50	5.6%
A	49	5.5%
s	39	4.3%
l	35	3.9%
o	33	3.7%
Other values (33)	350	39.0%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	656	73.1%
Uppercase Letter	185	20.6%
Space Separator	54	6.0%
Dash Punctuation	3	0.3%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
a	88	13.4%
e	74	11.3%
r	66	10.1%
i	60	9.1%
n	50	7.6%
s	39	5.9%
l	35	5.3%
o	33	5.0%
k	33	5.0%
c	23	3.5%
Other values (14)	155	23.6%

Uppercase Letter

Value	Count	Frequency (%)
A	49	26.5%
D	20	10.8%
G	17	9.2%
E	15	8.1%
T	14	7.6%
M	13	7.0%
H	13	7.0%
S	10	5.4%
B	7	3.8%
C	6	3.2%
Other values (7)	21	11.4%

Space Separator

Value	Count	Frequency (%)
	54	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	3	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	841	93.7%
Common	57	6.3%

Most frequent character per script

Latin

Value	Count	Frequency (%)
a	88	10.5%
e	74	8.8%
r	66	7.8%
i	60	7.1%
n	50	5.9%
A	49	5.8%
s	39	4.6%
l	35	4.2%
o	33	3.9%
k	33	3.9%
Other values (31)	314	37.3%

Common

Value	Count	Frequency (%)
	54	94.7%
-	3	5.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	898	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
a	88	9.8%
e	74	8.2%
r	66	7.3%
i	60	6.7%
	54	6.0%
n	50	5.6%
A	49	5.5%
s	39	4.3%
l	35	3.9%
o	33	3.7%
Other values (33)	350	39.0%

city
Categorical

Distinct	1
Distinct (%)	1.1%
Missing	0
Missing (%)	0.0%
Memory size	888.0 B

Lahore	95

Length

Max length	6
Median length	6
Mean length	6
Min length	6

Characters and Unicode

Total characters	570
Distinct characters	6
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Lahore
2nd row	Lahore
3rd row	Lahore
4th row	Lahore
5th row	Lahore

Common Values

Value	Count	Frequency (%)
Lahore	95	100.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
lahore	95	100.0%

Most occurring characters

Value	Count	Frequency (%)
L	95	16.7%
a	95	16.7%
h	95	16.7%
o	95	16.7%
r	95	16.7%
e	95	16.7%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	475	83.3%
Uppercase Letter	95	16.7%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
a	95	20.0%
h	95	20.0%
o	95	20.0%
r	95	20.0%
e	95	20.0%

Uppercase Letter

Value	Count	Frequency (%)
L	95	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	570	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
L	95	16.7%
a	95	16.7%
h	95	16.7%
o	95	16.7%
r	95	16.7%
e	95	16.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	570	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
L	95	16.7%
a	95	16.7%
h	95	16.7%
o	95	16.7%
r	95	16.7%
e	95	16.7%

province_name
Categorical

Distinct	1
Distinct (%)	1.1%
Missing	0
Missing (%)	0.0%
Memory size	888.0 B

Punjab	95

Length

Max length	6
Median length	6
Mean length	6
Min length	6

Characters and Unicode

Total characters	570
Distinct characters	6
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Punjab
2nd row	Punjab
3rd row	Punjab
4th row	Punjab
5th row	Punjab

Common Values

Value	Count	Frequency (%)
Punjab	95	100.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
punjab	95	100.0%

Most occurring characters

Value	Count	Frequency (%)
P	95	16.7%
u	95	16.7%
n	95	16.7%
j	95	16.7%
a	95	16.7%
b	95	16.7%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	475	83.3%
Uppercase Letter	95	16.7%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
u	95	20.0%
n	95	20.0%
j	95	20.0%
a	95	20.0%
b	95	20.0%

Uppercase Letter

Value	Count	Frequency (%)
P	95	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	570	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
P	95	16.7%
u	95	16.7%
n	95	16.7%
j	95	16.7%
a	95	16.7%
b	95	16.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	570	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
P	95	16.7%
u	95	16.7%
n	95	16.7%
j	95	16.7%
a	95	16.7%
b	95	16.7%

locality
Categorical

Distinct	28
Distinct (%)	29.5%
Missing	0
Missing (%)	0.0%
Memory size	888.0 B

Askari, Lahore, Punjab	31
Gulberg, Lahore, Punjab	12
DHA Defence, Lahore, Punjab	10
Bahria Town, Lahore, Punjab	6
EME Society, Lahore, Punjab	5
Other values (23)	31

Length

Max length	52
Median length	40
Mean length	25.452632
Min length	19

Characters and Unicode

Total characters	2418
Distinct characters	46
Distinct categories	5 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	17 ?
Unique (%)	17.9%

Sample

1st row	Model Town, Lahore, Punjab
2nd row	Multan Road, Lahore, Punjab
3rd row	Eden, Lahore, Punjab
4th row	Gulberg, Lahore, Punjab
5th row	EME Society, Lahore, Punjab

Common Values

Value	Count	Frequency (%)
Askari, Lahore, Punjab	31	32.6%
Gulberg, Lahore, Punjab	12	12.6%
DHA Defence, Lahore, Punjab	10	10.5%
Bahria Town, Lahore, Punjab	6	6.3%
EME Society, Lahore, Punjab	5	5.3%
Allama Iqbal Town, Lahore, Punjab	3	3.2%
Upper Mall, Lahore, Punjab	3	3.2%
Paragon City, Lahore, Punjab	2	2.1%
Model Town, Lahore, Punjab	2	2.1%
Eden, Lahore, Punjab	2	2.1%
Other values (18)	19	20.0%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
punjab	95	28.0%
lahore	95	28.0%
askari	31	9.1%
town	14	4.1%
gulberg	12	3.5%
dha	10	2.9%
defence	10	2.9%
society	8	2.4%
bahria	6	1.8%
eme	5	1.5%
Other values (34)	53	15.6%

Most occurring characters

Value	Count	Frequency (%)
a	278	11.5%
	244	10.1%
,	190	7.9%
e	169	7.0%
r	161	6.7%
n	145	6.0%
o	128	5.3%
u	116	4.8%
b	111	4.6%
h	107	4.4%
Other values (36)	769	31.8%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	1606	66.4%
Uppercase Letter	375	15.5%
Space Separator	244	10.1%
Other Punctuation	190	7.9%
Dash Punctuation	3	0.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
a	278	17.3%
e	169	10.5%
r	161	10.0%
n	145	9.0%
o	128	8.0%
u	116	7.2%
b	111	6.9%
h	107	6.7%
j	95	5.9%
i	60	3.7%
Other values (15)	236	14.7%

Uppercase Letter

Value	Count	Frequency (%)
P	100	26.7%
L	95	25.3%
A	49	13.1%
D	20	5.3%
G	17	4.5%
E	15	4.0%
T	14	3.7%
H	13	3.5%
M	13	3.5%
S	10	2.7%
Other values (8)	29	7.7%

Space Separator

Value	Count	Frequency (%)
	244	100.0%

Other Punctuation

Value	Count	Frequency (%)
,	190	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	3	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	1981	81.9%
Common	437	18.1%

Most frequent character per script

Latin

Value	Count	Frequency (%)
a	278	14.0%
e	169	8.5%
r	161	8.1%
n	145	7.3%
o	128	6.5%
u	116	5.9%
b	111	5.6%
h	107	5.4%
P	100	5.0%
L	95	4.8%
Other values (33)	571	28.8%

Common

Value	Count	Frequency (%)
	244	55.8%
,	190	43.5%
-	3	0.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	2418	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
a	278	11.5%
	244	10.1%
,	190	7.9%
e	169	7.0%
r	161	6.7%
n	145	6.0%
o	128	5.3%
u	116	4.8%
b	111	4.6%
h	107	4.4%
Other values (36)	769	31.8%

latitude
Real number (ℝ)

Distinct	57
Distinct (%)	60.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	31.501448

Minimum	31.37108
Maximum	31.717279
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	888.0 B

Quantile statistics

Minimum	31.37108
5-th percentile	31.379518
Q1	31.467691
median	31.522361
Q3	31.536068
95-th percentile	31.556202
Maximum	31.717279
Range	0.34619872
Interquartile range (IQR)	0.068377

Descriptive statistics

Standard deviation	0.057218636
Coefficient of variation (CV)	0.0018163812
Kurtosis	1.5960675
Mean	31.501448
Median Absolute Deviation (MAD)	0.019753
Skewness	-0.22426899
Sum	2992.6375
Variance	0.0032739724
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
31.533161	8	8.4%
31.537458	6	6.3%
31.469155	5	5.3%
31.53327	5	5.3%
31.536068	4	4.2%
31.537239	3	3.2%
31.374195	3	3.2%
31.533849	3	3.2%
31.542114	3	3.2%
31.518337	2	2.1%
Other values (47)	53	55.8%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
31.37108	1	1.1%
31.374195	3	3.2%
31.374414	1	1.1%
31.381706	1	1.1%
31.400096	1	1.1%
31.402513	1	1.1%
31.40537	1	1.1%
31.431593	1	1.1%
31.434668	1	1.1%
31.437744	2	2.1%

Value	Count	Frequency (%)
31.71727872	1	1.1%
31.597234	1	1.1%
31.590234	1	1.1%
31.57443055	1	1.1%
31.567912	1	1.1%
31.551184	1	1.1%
31.54913521	1	1.1%
31.543431	1	1.1%
31.542114	3	3.2%
31.539206	1	1.1%

longitude
Real number (ℝ)

Distinct	58
Distinct (%)	61.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	74.357936

Minimum	74.177749
Maximum	74.474513
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	888.0 B

Quantile statistics

Minimum	74.177749
5-th percentile	74.191482
Q1	74.30294
median	74.385309
Q3	74.419481
95-th percentile	74.470553
Maximum	74.474513
Range	0.296764
Interquartile range (IQR)	0.116541

Descriptive statistics

Standard deviation	0.083130273
Coefficient of variation (CV)	0.0011179745
Kurtosis	-0.52166294
Mean	74.357936
Median Absolute Deviation (MAD)	0.039761
Skewness	-0.73803026
Sum	7064.0039
Variance	0.0069106423
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
74.419481	8	8.4%
74.413323	6	6.3%
74.470553	5	5.3%
74.41358	5	5.3%
74.408666	4	4.2%
74.420211	3	3.2%
74.191482	3	3.2%
74.409633	3	3.2%
74.355898	3	3.2%
74.348202	2	2.1%
Other values (48)	53	55.8%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
74.177749	1	1.1%
74.17998	1	1.1%
74.190316	1	1.1%
74.191482	3	3.2%
74.195294	1	1.1%
74.209685	2	2.1%
74.21349	2	2.1%
74.214005	1	1.1%
74.224648	1	1.1%
74.239683	1	1.1%

Value	Count	Frequency (%)
74.474513	1	1.1%
74.470553	5	5.3%
74.456184	1	1.1%
74.45599191	1	1.1%
74.451342	1	1.1%
74.445906	1	1.1%
74.44369633	1	1.1%
74.440012	1	1.1%
74.429569	1	1.1%
74.427137	1	1.1%

baths
Real number (ℝ)

HIGH CORRELATION
ZEROS

Distinct	8
Distinct (%)	8.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	4.3263158

Minimum	0
Maximum	8
Zeros	16
Zeros (%)	16.8%
Negative	0
Negative (%)	0.0%
Memory size	888.0 B

Quantile statistics

Minimum	0
5-th percentile	0
Q1	3.5
median	5
Q3	6
95-th percentile	7
Maximum	8
Range	8
Interquartile range (IQR)	2.5

Descriptive statistics

Standard deviation	2.3083664
Coefficient of variation (CV)	0.53356401
Kurtosis	-0.35517021
Mean	4.3263158
Median Absolute Deviation (MAD)	1
Skewness	-0.83280733
Sum	411
Variance	5.3285554
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=8)

Value	Count	Frequency (%)
5	27	28.4%
6	22	23.2%
0	16	16.8%
4	11	11.6%
7	8	8.4%
3	4	4.2%
2	4	4.2%
8	3	3.2%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	16	16.8%
2	4	4.2%
3	4	4.2%
4	11	11.6%
5	27	28.4%
6	22	23.2%
7	8	8.4%
8	3	3.2%

Value	Count	Frequency (%)
8	3	3.2%
7	8	8.4%
6	22	23.2%
5	27	28.4%
4	11	11.6%
3	4	4.2%
2	4	4.2%
0	16	16.8%

area
Categorical

Distinct	29
Distinct (%)	30.5%
Missing	0
Missing (%)	0.0%
Memory size	888.0 B

10 Marla	33
1 Kanal	21
2 Kanal	5
3 Marla	3
12 Marla	3
Other values (24)	30

Length

Max length	9
Median length	8
Mean length	7.6736842
Min length	7

Characters and Unicode

Total characters	729
Distinct characters	18
Distinct categories	5 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	19 ?
Unique (%)	20.0%

Sample

1st row	6 Kanal
2nd row	1 Kanal
3rd row	9 Marla
4th row	1 Kanal
5th row	1 Kanal

Common Values

Value	Count	Frequency (%)
10 Marla	33	34.7%
1 Kanal	21	22.1%
2 Kanal	5	5.3%
3 Marla	3	3.2%
12 Marla	3	3.2%
17 Marla	3	3.2%
18 Marla	2	2.1%
2 Marla	2	2.1%
1.1 Kanal	2	2.1%
8 Kanal	2	2.1%
Other values (19)	19	20.0%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
marla	59	31.1%
kanal	36	18.9%
10	34	17.9%
1	21	11.1%
2	7	3.7%
3	3	1.6%
12	3	1.6%
17	3	1.6%
8	3	1.6%
6	2	1.1%
Other values (16)	19	10.0%

Most occurring characters

Value	Count	Frequency (%)
a	190	26.1%
	95	13.0%
l	95	13.0%
1	71	9.7%
M	59	8.1%
r	59	8.1%
K	36	4.9%
n	36	4.9%
0	34	4.7%
2	13	1.8%
Other values (8)	41	5.6%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	380	52.1%
Decimal Number	149	20.4%
Space Separator	95	13.0%
Uppercase Letter	95	13.0%
Other Punctuation	10	1.4%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	71	47.7%
0	34	22.8%
2	13	8.7%
7	7	4.7%
8	6	4.0%
5	6	4.0%
4	4	2.7%
3	3	2.0%
6	3	2.0%
9	2	1.3%

Lowercase Letter

Value	Count	Frequency (%)
a	190	50.0%
l	95	25.0%
r	59	15.5%
n	36	9.5%

Uppercase Letter

Value	Count	Frequency (%)
M	59	62.1%
K	36	37.9%

Space Separator

Value	Count	Frequency (%)
	95	100.0%

Other Punctuation

Value	Count	Frequency (%)
.	10	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	475	65.2%
Common	254	34.8%

Most frequent character per script

Common

Value	Count	Frequency (%)
	95	37.4%
1	71	28.0%
0	34	13.4%
2	13	5.1%
.	10	3.9%
7	7	2.8%
8	6	2.4%
5	6	2.4%
4	4	1.6%
3	3	1.2%
Other values (2)	5	2.0%

Latin

Value	Count	Frequency (%)
a	190	40.0%
l	95	20.0%
M	59	12.4%
r	59	12.4%
K	36	7.6%
n	36	7.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	729	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
a	190	26.1%
	95	13.0%
l	95	13.0%
1	71	9.7%
M	59	8.1%
r	59	8.1%
K	36	4.9%
n	36	4.9%
0	34	4.7%
2	13	1.8%
Other values (8)	41	5.6%

area_marla
Real number (ℝ)

Distinct	29
Distinct (%)	30.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	23.109474

Minimum	2
Maximum	200
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	888.0 B

Quantile statistics

Minimum	2
5-th percentile	3
Q1	10
median	10
Q3	20
95-th percentile	101.8
Maximum	200
Range	198
Interquartile range (IQR)	10

Descriptive statistics

Standard deviation	34.374276
Coefficient of variation (CV)	1.4874539
Kurtosis	12.650675
Mean	23.109474
Median Absolute Deviation (MAD)	6
Skewness	3.5271151
Sum	2195.4
Variance	1181.5909
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=29)

Value	Count	Frequency (%)
10	33	34.7%
20	21	22.1%
40	5	5.3%
3	3	3.2%
12	3	3.2%
17	3	3.2%
18	2	2.1%
2	2	2.1%
22	2	2.1%
160	2	2.1%
Other values (19)	19	20.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
2	2	2.1%
2.5	1	1.1%
3	3	3.2%
4	1	1.1%
5	1	1.1%
5.5	1	1.1%
6	1	1.1%
7	1	1.1%
7.5	1	1.1%
8	1	1.1%

Value	Count	Frequency (%)
200	1	1.1%
160	2	2.1%
130	1	1.1%
120	1	1.1%
94	1	1.1%
80	1	1.1%
40	5	5.3%
24	1	1.1%
22	2	2.1%
20	21	22.1%

area_sqft
Real number (ℝ)

Distinct	29
Distinct (%)	30.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	6291.5771

Minimum	544.5
Maximum	54450.2
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	888.0 B

Quantile statistics

Minimum	544.5
5-th percentile	816.75
Q1	2722.51
median	2722.51
Q3	5445.02
95-th percentile	27715.149
Maximum	54450.2
Range	53905.7
Interquartile range (IQR)	2722.51

Descriptive statistics

Standard deviation	9358.4311
Coefficient of variation (CV)	1.4874539
Kurtosis	12.650675
Mean	6291.5771
Median Absolute Deviation (MAD)	1633.51
Skewness	3.5271151
Sum	597699.82
Variance	87580233
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=29)

Value	Count	Frequency (%)
2722.51	33	34.7%
5445.02	21	22.1%
10890.04	5	5.3%
816.75	3	3.2%
3267.01	3	3.2%
4628.27	3	3.2%
4900.52	2	2.1%
544.5	2	2.1%
5989.52	2	2.1%
43560.16	2	2.1%
Other values (19)	19	20.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
544.5	2	2.1%
680.63	1	1.1%
816.75	3	3.2%
1089	1	1.1%
1361.25	1	1.1%
1497.38	1	1.1%
1633.51	1	1.1%
1905.76	1	1.1%
2041.88	1	1.1%
2178.01	1	1.1%

Value	Count	Frequency (%)
54450.2	1	1.1%
43560.16	2	2.1%
35392.63	1	1.1%
32670.12	1	1.1%
25591.59	1	1.1%
21780.08	1	1.1%
10890.04	5	5.3%
6534.02	1	1.1%
5989.52	2	2.1%
5445.02	21	22.1%

purpose
Categorical

Distinct	1
Distinct (%)	1.1%
Missing	0
Missing (%)	0.0%
Memory size	888.0 B

For Sale	95

Length

Max length	8
Median length	8
Mean length	8
Min length	8

Characters and Unicode

Total characters	760
Distinct characters	8
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	For Sale
2nd row	For Sale
3rd row	For Sale
4th row	For Sale
5th row	For Sale

Common Values

Value	Count	Frequency (%)
For Sale	95	100.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
for	95	50.0%
sale	95	50.0%

Most occurring characters

Value	Count	Frequency (%)
F	95	12.5%
o	95	12.5%
r	95	12.5%
	95	12.5%
S	95	12.5%
a	95	12.5%
l	95	12.5%
e	95	12.5%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	475	62.5%
Uppercase Letter	190	25.0%
Space Separator	95	12.5%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
o	95	20.0%
r	95	20.0%
a	95	20.0%
l	95	20.0%
e	95	20.0%

Uppercase Letter

Value	Count	Frequency (%)
F	95	50.0%
S	95	50.0%

Space Separator

Value	Count	Frequency (%)
	95	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	665	87.5%
Common	95	12.5%

Most frequent character per script

Latin

Value	Count	Frequency (%)
F	95	14.3%
o	95	14.3%
r	95	14.3%
S	95	14.3%
a	95	14.3%
l	95	14.3%
e	95	14.3%

Common

Value	Count	Frequency (%)
	95	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	760	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
F	95	12.5%
o	95	12.5%
r	95	12.5%
	95	12.5%
S	95	12.5%
a	95	12.5%
l	95	12.5%
e	95	12.5%

bedrooms
Real number (ℝ)

HIGH CORRELATION
ZEROS

Distinct	7
Distinct (%)	7.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	3.9263158

Minimum	0
Maximum	8
Zeros	12
Zeros (%)	12.6%
Negative	0
Negative (%)	0.0%
Memory size	888.0 B

Quantile statistics

Minimum	0
5-th percentile	0
Q1	3
median	4
Q3	5
95-th percentile	6
Maximum	8
Range	8
Interquartile range (IQR)	2

Descriptive statistics

Standard deviation	1.8232663
Coefficient of variation (CV)	0.46437078
Kurtosis	0.6562661
Mean	3.9263158
Median Absolute Deviation (MAD)	1
Skewness	-0.89984563
Sum	373
Variance	3.3243001
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=7)

Value	Count	Frequency (%)
5	31	32.6%
4	28	29.5%
0	12	12.6%
3	10	10.5%
6	9	9.5%
2	3	3.2%
8	2	2.1%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	12	12.6%
2	3	3.2%
3	10	10.5%
4	28	29.5%
5	31	32.6%
6	9	9.5%
8	2	2.1%

Value	Count	Frequency (%)
8	2	2.1%
6	9	9.5%
5	31	32.6%
4	28	29.5%
3	10	10.5%
2	3	3.2%
0	12	12.6%

date_added
Categorical

Distinct	22
Distinct (%)	23.2%
Missing	0
Missing (%)	0.0%
Memory size	888.0 B

06-18-2019	32
07/03/2019	10
05/03/2019	10
04/04/2019	7
06-25-2019	7
Other values (17)	29

Length

Max length	10
Median length	10
Mean length	10
Min length	10

Characters and Unicode

Total characters	950
Distinct characters	12
Distinct categories	3 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	11 ?
Unique (%)	11.6%

Sample

1st row	07-17-2019
2nd row	10/06/2018
3rd row	07/03/2019
4th row	06/02/2019
5th row	07/03/2019

Common Values

Value	Count	Frequency (%)
06-18-2019	32	33.7%
07/03/2019	10	10.5%
05/03/2019	10	10.5%
04/04/2019	7	7.4%
06-25-2019	7	7.4%
04/03/2019	6	6.3%
06/11/2019	3	3.2%
02/03/2019	3	3.2%
12/05/2018	2	2.1%
06/02/2019	2	2.1%
Other values (12)	13	13.7%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
06-18-2019	32	33.7%
05/03/2019	10	10.5%
07/03/2019	10	10.5%
04/04/2019	7	7.4%
06-25-2019	7	7.4%
04/03/2019	6	6.3%
06/11/2019	3	3.2%
02/03/2019	3	3.2%
12/05/2018	2	2.1%
06/02/2019	2	2.1%
Other values (12)	13	13.7%

Most occurring characters

Value	Count	Frequency (%)
0	236	24.8%
1	145	15.3%
2	112	11.8%
/	102	10.7%
9	91	9.6%
-	88	9.3%
6	50	5.3%
8	37	3.9%
3	32	3.4%
4	22	2.3%
Other values (2)	35	3.7%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	760	80.0%
Other Punctuation	102	10.7%
Dash Punctuation	88	9.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	236	31.1%
1	145	19.1%
2	112	14.7%
9	91	12.0%
6	50	6.6%
8	37	4.9%
3	32	4.2%
4	22	2.9%
5	21	2.8%
7	14	1.8%

Other Punctuation

Value	Count	Frequency (%)
/	102	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	88	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	950	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	236	24.8%
1	145	15.3%
2	112	11.8%
/	102	10.7%
9	91	9.6%
-	88	9.3%
6	50	5.3%
8	37	3.9%
3	32	3.4%
4	22	2.3%
Other values (2)	35	3.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	950	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	236	24.8%
1	145	15.3%
2	112	11.8%
/	102	10.7%
9	91	9.6%
-	88	9.3%
6	50	5.3%
8	37	3.9%
3	32	3.4%
4	22	2.3%
Other values (2)	35	3.7%

year
Real number (ℝ)

Distinct	2
Distinct (%)	2.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2018.9579

Minimum	2018
Maximum	2019
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	888.0 B

Quantile statistics

Minimum	2018
5-th percentile	2019
Q1	2019
median	2019
Q3	2019
95-th percentile	2019
Maximum	2019
Range	1
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.20189472
Coefficient of variation (CV)	9.9999471 × 10^-5
Kurtosis	19.887875
Mean	2018.9579
Median Absolute Deviation (MAD)	0
Skewness	-4.6335232
Sum	191801
Variance	0.040761478
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=2)

Value	Count	Frequency (%)
2019	91	95.8%
2018	4	4.2%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
2018	4	4.2%
2019	91	95.8%

Value	Count	Frequency (%)
2019	91	95.8%
2018	4	4.2%

month
Real number (ℝ)

Distinct	10
Distinct (%)	10.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	5.6736842

Minimum	1
Maximum	12
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	888.0 B

Quantile statistics

Minimum	1
5-th percentile	2
Q1	5
median	6
Q3	6
95-th percentile	7
Maximum	12
Range	11
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	1.7891048
Coefficient of variation (CV)	0.31533386
Kurtosis	3.8052285
Mean	5.6736842
Median Absolute Deviation (MAD)	0
Skewness	0.54053379
Sum	539
Variance	3.2008959
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
6	48	50.5%
7	13	13.7%
4	13	13.7%
5	10	10.5%
2	4	4.2%
1	2	2.1%
12	2	2.1%
10	1	1.1%
3	1	1.1%
11	1	1.1%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1	2	2.1%
2	4	4.2%
3	1	1.1%
4	13	13.7%
5	10	10.5%
6	48	50.5%
7	13	13.7%
10	1	1.1%
11	1	1.1%
12	2	2.1%

Value	Count	Frequency (%)
12	2	2.1%
11	1	1.1%
10	1	1.1%
7	13	13.7%
6	48	50.5%
5	10	10.5%
4	13	13.7%
3	1	1.1%
2	4	4.2%
1	2	2.1%

day
Real number (ℝ)

Distinct	14
Distinct (%)	14.7%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	11.378947

Minimum	1
Maximum	30
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	888.0 B

Quantile statistics

Minimum	1
5-th percentile	3
Q1	3
median	11
Q3	18
95-th percentile	25
Maximum	30
Range	29
Interquartile range (IQR)	15

Descriptive statistics

Standard deviation	8.4352086
Coefficient of variation (CV)	0.74129955
Kurtosis	-1.315944
Mean	11.378947
Median Absolute Deviation (MAD)	7
Skewness	0.34121383
Sum	1081
Variance	71.152744
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=14)

Value	Count	Frequency (%)
18	33	34.7%
3	29	30.5%
4	9	9.5%
25	7	7.4%
5	4	4.2%
11	3	3.2%
2	2	2.1%
30	2	2.1%
17	1	1.1%
6	1	1.1%
Other values (4)	4	4.2%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1	1	1.1%
2	2	2.1%
3	29	30.5%
4	9	9.5%
5	4	4.2%
6	1	1.1%
10	1	1.1%
11	3	3.2%
12	1	1.1%
17	1	1.1%

Value	Count	Frequency (%)
30	2	2.1%
26	1	1.1%
25	7	7.4%
18	33	34.7%
17	1	1.1%
12	1	1.1%
11	3	3.2%
10	1	1.1%
6	1	1.1%
5	4	4.2%

Auto

The auto setting is an interpretable pairwise column metric of the following mapping:

Variable_type-Variable_type : Method, Range
Categorical-Categorical : Cramer's V, [0,1]
Numerical-Categorical : Cramer's V, [0,1] (using a discretized numerical column)
Numerical-Numerical : Spearman's ρ, [-1,1]

The number of bins used in the discretization for the Numerical-Categorical column pair can be changed using config.correlations["auto"].n_bins. The number of bins affects the granularity of the association you wish to measure.

This configuration uses the recommended metric for each pair of columns.

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Count
Matrix

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

First rows
Last rows

	property_id	location_id	page_url	property_type	price	price_bin	location	city	province_name	locality	latitude	longitude	baths	area	area_marla	area_sqft	purpose	bedrooms	date_added	year	month	day
0	347795	8	https://www.zameen.com/Property/lahore_model_town_6_kanal_excellent_house_for_sale_in_model_town-347795-8-1.html	House	220000000	Very High	Model Town	Lahore	Punjab	Model Town, Lahore, Punjab	31.483869	74.325686	0	6 Kanal	120.0	32670.12	For Sale	0	07-17-2019	2019	7	17
1	482892	48	https://www.zameen.com/Property/lahore_multan_road_1_kanal_house_for_sale-482892-48-1.html	House	40000000	Very High	Multan Road	Lahore	Punjab	Multan Road, Lahore, Punjab	31.431593	74.179980	5	1 Kanal	20.0	5445.02	For Sale	5	10/06/2018	2018	10	6
2	555962	75	https://www.zameen.com/Property/eden_eden_avenue_9_marla_house_for_sale-555962-75-1.html	House	9500000	Low	Eden	Lahore	Punjab	Eden, Lahore, Punjab	31.499348	74.416959	0	9 Marla	9.0	2450.26	For Sale	3	07/03/2019	2019	7	3
3	785289	3102	https://www.zameen.com/Property/gulberg_paf_falcon_complex_matz_service_offer_1_kanal_house_for_sale-785289-3102-1.html	House	52000000	Very High	Gulberg	Lahore	Punjab	Gulberg, Lahore, Punjab	31.495909	74.350569	6	1 Kanal	20.0	5445.02	For Sale	5	06/02/2019	2019	6	2
4	983065	3749	https://www.zameen.com/Property/eme_society_eme_society_block_e_house_for_sale-983065-3749-1.html	House	32500000	High	EME Society	Lahore	Punjab	EME Society, Lahore, Punjab	31.439978	74.209685	0	1 Kanal	20.0	5445.02	For Sale	5	07/03/2019	2019	7	3
5	983066	3745	https://www.zameen.com/Property/eme_society_eme_society_block_a_house_for_sale-983066-3745-1.html	House	31500000	High	EME Society	Lahore	Punjab	EME Society, Lahore, Punjab	31.437744	74.213490	0	1 Kanal	20.0	5445.02	For Sale	6	07/03/2019	2019	7	3
6	1286643	3733	https://www.zameen.com/Property/eden_eden_palace_villas_7_5_marla_luxury_house_is_available_for_sale-1286643-3733-1.html	House	13500000	Medium	Eden	Lahore	Punjab	Eden, Lahore, Punjab	31.441113	74.239683	4	7.5 Marla	7.5	2041.88	For Sale	4	04/04/2019	2019	4	4
7	1402784	514	https://www.zameen.com/Property/lahore_upper_mall_commercial_old_house_for_sale_upper_mall_lahore_excellent_location-1402784-514-1.html	House	87500000	Very High	Upper Mall	Lahore	Punjab	Upper Mall, Lahore, Punjab	31.542114	74.355898	5	1.2 Kanal	24.0	6534.02	For Sale	4	06-30-2019	2019	6	30
8	1606710	69	https://www.zameen.com/Property/lahore_cavalry_ground_10_marla_house_is_available_for_sale-1606710-69-1.html	House	16500000	High	Cavalry Ground	Lahore	Punjab	Cavalry Ground, Lahore, Punjab	31.500557	74.367730	0	10 Marla	10.0	2722.51	For Sale	4	04/04/2019	2019	4	4
9	1646880	1781	https://www.zameen.com/Property/bahria_town_sector_b_bahria_town_umar_block_double_storey_house_for_sale-1646880-1781-1.html	House	18500000	High	Bahria Town	Lahore	Punjab	Bahria Town, Lahore, Punjab	31.381706	74.195294	0	10 Marla	10.0	2722.51	For Sale	0	07/04/2019	2019	7	4

	property_id	location_id	page_url	property_type	price	price_bin	location	city	province_name	locality	latitude	longitude	baths	area	area_marla	area_sqft	purpose	bedrooms	date_added	year	month	day
85	4536854	3852	https://www.zameen.com/Property/gulberg_main_boulevard_gulberg_commercialized_piece_of_property_house_for_sale-4536854-3852-1.html	House	1200000000	Very High	Gulberg	Lahore	Punjab	Gulberg, Lahore, Punjab	31.519435	74.345548	0	8 Kanal	160.0	43560.16	For Sale	0	04/04/2019	2019	4	4
86	4557799	3850	https://www.zameen.com/Property/gulberg_mm_alam_road_shopping_paradise_of_lahore_house_for_sale-4557799-3850-1.html	House	380000000	Very High	Gulberg	Lahore	Punjab	Gulberg, Lahore, Punjab	31.510471	74.350526	0	2 Kanal	40.0	10890.04	For Sale	0	05/03/2019	2019	5	3
87	4560911	496	https://www.zameen.com/Property/mozang_mozang_chungi_al_qader_center_ground_floor_new_apartment_for_sale-4560911-496-1.html	Flat	3200000	Low	Mozang	Lahore	Punjab	Mozang, Lahore, Punjab	31.549135	74.315117	2	3 Marla	3.0	816.75	For Sale	2	07/03/2019	2019	7	3
88	4570988	1447	https://www.zameen.com/Property/dha_defence_dha_phase_5_original_faisal_rasool_brand_new_classical_bungalow-4570988-1447-1.html	House	59800000	Very High	DHA Defence	Lahore	Punjab	DHA Defence, Lahore, Punjab	31.462493	74.409342	7	1 Kanal	20.0	5445.02	For Sale	6	05/03/2019	2019	5	3
89	4677101	8172	https://www.zameen.com/Property/dha_defence_defence_raya_dha_raya_2_kanal_facing_golf_course_fully_basement_house_for_sale-4677101-8172-1.html	House	66000000	Very High	DHA Defence	Lahore	Punjab	DHA Defence, Lahore, Punjab	31.469155	74.470553	6	2 Kanal	40.0	10890.04	For Sale	6	06-25-2019	2019	6	25
90	4747413	154	https://www.zameen.com/Property/gulberg_zafar_ali_road_6_kanal_house_for_sale_on_zafar_ali_road_mall_road_upper_mall_lahore_excellent_location-4747413-154-1.html	House	360000000	Very High	Gulberg	Lahore	Punjab	Gulberg, Lahore, Punjab	31.538420	74.352357	7	10 Kanal	200.0	54450.20	For Sale	5	06-30-2019	2019	6	30
91	4907568	514	https://www.zameen.com/Property/lahore_upper_mall_4_kanal__house_for_sale_upper_mall_lahore-4907568-514-1.html	House	160000000	Very High	Upper Mall	Lahore	Punjab	Upper Mall, Lahore, Punjab	31.542114	74.355898	6	1 Kanal	20.0	5445.02	For Sale	5	01-18-2019	2019	1	18
92	4940629	8	https://www.zameen.com/Property/lahore_model_town_3_marla_house_for_sale-4940629-8-1.html	House	8000000	Low	Model Town	Lahore	Punjab	Model Town, Lahore, Punjab	31.473884	74.329080	3	3 Marla	3.0	816.75	For Sale	2	07/03/2019	2019	7	3
93	4951451	7	https://www.zameen.com/Property/lahore_gulberg_blue_zone_house_for_sale-4951451-7-1.html	House	480000000	Very High	Gulberg	Lahore	Punjab	Gulberg, Lahore, Punjab	31.522361	74.347172	0	4 Kanal	80.0	21780.08	For Sale	0	05/03/2019	2019	5	3
94	5019310	1534	https://www.zameen.com/Property/garden_town_garden_town_ahmed_block_purely_residential_apartments_for_sale-5019310-1534-1.html	Flat	22500000	Very High	Garden Town	Lahore	Punjab	Garden Town, Lahore, Punjab	31.507800	74.318733	0	7 Marla	7.0	1905.76	For Sale	0	04/03/2019	2019	4	3

Overview

Variables

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Decimal Number

Other Punctuation

Connector Punctuation

Dash Punctuation

Uppercase Letter

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Most occurring scripts

Most frequent character per script

Latin

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Space Separator

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Space Separator

Dash Punctuation

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Most occurring scripts

Most frequent character per script

Latin

Most occurring blocks

Most frequent character per block

ASCII